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import streamlit as st |
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from streamlit_float import * |
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from streamlit_antd_components import * |
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import pandas as pd |
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import logging |
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import io |
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import matplotlib.pyplot as plt |
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logger = logging.getLogger(__name__) |
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from .discourse_process import perform_discourse_analysis |
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from .discourse_interface import display_discourse_results |
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from ..utils.widget_utils import generate_unique_key |
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from ..database.discourse_mongo_db import store_student_discourse_result |
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from ..database.chat_mongo_db import store_chat_history, get_chat_history |
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def fig_to_bytes(fig): |
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"""Convierte una figura de matplotlib a bytes.""" |
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try: |
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buf = io.BytesIO() |
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fig.savefig(buf, format='png', dpi=300, bbox_inches='tight') |
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buf.seek(0) |
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return buf.getvalue() |
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except Exception as e: |
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logger.error(f"Error en fig_to_bytes: {str(e)}") |
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return None |
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def display_discourse_live_interface(lang_code, nlp_models, discourse_t): |
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""" |
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Interfaz para el análisis del discurso en vivo |
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""" |
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try: |
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if analyze_button and text_input1 and text_input2: |
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try: |
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with st.spinner(discourse_t.get('processing', 'Procesando...')): |
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result = perform_discourse_analysis( |
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text_input1, |
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text_input2, |
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nlp_models[lang_code], |
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lang_code |
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) |
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if result['success']: |
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for graph_key in ['graph1', 'graph2']: |
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if graph_key in result and result[graph_key] is not None: |
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bytes_key = f'{graph_key}_bytes' |
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graph_bytes = fig_to_bytes(result[graph_key]) |
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if graph_bytes: |
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result[bytes_key] = graph_bytes |
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plt.close(result[graph_key]) |
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st.session_state.discourse_live_state['last_result'] = result |
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st.session_state.discourse_live_state['analysis_count'] += 1 |
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st.session_state.discourse_live_state['text_changed'] = False |
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store_result = store_student_discourse_result( |
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st.session_state.username, |
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text_input1, |
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text_input2, |
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result |
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) |
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if not store_result: |
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logger.warning("No se pudo guardar el análisis en la base de datos") |
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else: |
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st.error(result.get('message', 'Error en el análisis')) |
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except Exception as e: |
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logger.error(f"Error en análisis: {str(e)}") |
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st.error(discourse_t.get('error_processing', f'Error al procesar el texto: {str(e)}')) |
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with result_col: |
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st.subheader(discourse_t.get('live_results', 'Resultados en vivo')) |
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if 'last_result' in st.session_state.discourse_live_state and \ |
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st.session_state.discourse_live_state['last_result'] is not None: |
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result = st.session_state.discourse_live_state['last_result'] |
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if all(key in result for key in ['graph1', 'graph2', 'graph1_bytes', 'graph2_bytes']): |
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display_discourse_results(result, lang_code, discourse_t) |
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else: |
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logger.error(f"Faltan gráficos en el resultado: {list(result.keys())}") |
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st.error(discourse_t.get('missing_graphs', 'Error: No se pudieron generar todos los gráficos')) |
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elif st.session_state.discourse_live_state.get('text_changed', False): |
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st.info(discourse_t.get('changes_pending', |
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'Los textos han cambiado. Presione Analizar para ver los nuevos resultados.')) |
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else: |
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st.info(discourse_t.get('initial_message', |
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'Ingrese los textos y presione Analizar para ver los resultados.')) |
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except Exception as e: |
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logger.error(f"Error general en interfaz del discurso en vivo: {str(e)}") |
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st.error(discourse_t.get('general_error', "Se produjo un error. Por favor, intente de nuevo.")) |
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